融合改进鲸鱼算法解缠的梧州市地面沉降InSAR监测

InSAR Monitoring of Ground Subsidence in Wuzhou CityIncorporating Improved Whale Algorithm Untangling

针对基于InSAR地面沉降研究中干涉图解缠易陷入局部最优及地面沉降影响因子较多且复杂的情况,提出了一种结合全局鲸鱼算法寻优的InSAR解缠方法并以广西壮族自治区梧州市为研究区,构建人类扰动指数,探索其2018—2023年地面沉降状况及分析其驱动力因子。结果表明,改进鲸鱼优化算法从全局角度寻找枝切线最短路径,有效避免了陷入局部最优的问题。基于上述解缠方法获取了2018—2023年研究区地面沉降状况,并选取两个特征区域探究影响地面沉降的驱动力因子。经相关性分析,研究区地面沉降与城市扩张及重要交通枢纽建设密切相关,两个特征区域地面沉降速率与梧州市区建设用地面积的拟合优度R 2分别为0.9386和0.9842。本文研究结果可以为研究区城市规划建设及应急防灾提供决策支持。

In response to the situation that interferogram unwinding in InSAR-based ground subsidence research is prone to fall into local optimum and there are many and complex ground subsidence influence factors,this paper proposes an InSAR unwinding method combined with global whale algorithm to find the optimum and uses Wuzhou city of Guangxi Zhuang Autonomous Region as the study area to construct human disturbance index to explore its ground subsidence condition and analyze its driving factors in 2018-2023.The results show that the improved whale optimization algorithm finds the shortest path of branch tangents from a global perspective,effectively avoiding the problem of falling into local optimum.Based on the above-mentioned untangling method,this paper obtains the ground settlement condition in the study area from 2018-2023 and selects two characteristic regions to explore the driving factors affecting ground settlement,and after correlation analysis,the ground settlement in the study area is closely related to urban expansion and the construction of important transportation hubs,and the goodness-of-fit R 2 of the ground settlement rate in the two characteristic regions and the construction land area in Wuzhou city are 0.9386 and 0.9842,respectively.The results of this study can provide decision support for urban planning,construction and emergency disaster prevention in the study area.